Coal-bed gas well fracturing crack scale prediction method

Abstract

The invention relates to the field of fracture prediction, in particular to a coal-bed gas well fracturing fracture scale prediction method, which comprises the following steps of: establishing a relationship between a filtration coefficient and a burial depth according to a PKN model to obtain a support fracture length; establishing a relation between the hydraulic fracture length and the actually measured support fracture length according to the support fracture length; based on the relation between the hydraulic fracture length and the actually-measured support fracture length, the relation between the micro-seismic monitoring fracture length and the actually-measured support fracture length is established. According to the method, the coal-bed gas well fracturing fracture scale can be accurately predicted through the obtained support fracture length, the hydraulic fracture length and the microseismic monitoring fracture length. And the prediction precision and the fracturing design efficiency are remarkably improved by dynamically correcting the filtration coefficient and quantifying the multi-fracture proportional relation.

Description

Technical Field

[0001] The present invention relates to the field of crack prediction, and in particular to a method for predicting the scale of fractures in coalbed methane wells. Background Art

[0002] During the hydraulic fracturing process, proppant, fracturing fluid and stress will expand outward around the wellbore. Different monitoring methods will produce different detection results. Therefore, it is important to distinguish different types of cracks in the monitoring or prediction of crack expansion range. To this end, the three types of hydraulic fracturing cracks are identified and distinguished as follows: Figure 1 As shown:

[0003] (1) Propped fractures: fractures filled or spread by proppant, which have the smallest range. Their range and distribution characteristics can be directly obtained through downhole measurement and dissection.

[0004] (2) Hydraulic fractures: fractures formed by the loss of fracturing fluid. The scale of the fractures is the range of the spread of the fracturing fluid. The length of the fractures is between the supporting fractures and the monitoring fractures. The expansion range of the hydraulic fractures can be inferred by detecting the arrival position of the fracturing fluid.

[0005] (3) Monitoring cracks: The stress or vibration propagation range caused by hydraulic fracturing monitored by ground microseismic means during fracturing, which is the largest range.

[0006] Currently, the main hydraulic fracturing fracture models include the PKN model and the KGD model. Based on these models, numerous researchers have proposed different fracture models. The PKN and KGD models each have their own advantages and disadvantages, and their application conditions differ. In the PKN model, the elasticity of the fracture is primarily in the vertical plane perpendicular to the longitudinal direction. Deformation in the horizontal plane and the vertical plane is combined only by the flow resistance of the liquid, while the toughness of the rock in the longitudinal direction is ignored. The KGD model considers the rock toughness and flow resistance in the horizontal plane and establishes a balance between the two, but ignores the rock toughness in the vertical plane. Generally speaking, the PKN model is applicable when the aspect ratio is much greater than 1, while the KGD model is suitable for situations with a smaller aspect ratio, that is, when the construction time is short or the filtration coefficient is small.

[0007] Currently, the PKN model and KGD model ignore horizontal / vertical rock toughness, respectively, leading to errors in fracture length prediction (e.g., the PKN model is applicable to fractures with aspect ratios far greater than 1, while the KGD model is applicable to short-time / low filtration scenarios). Existing models do not correlate the filtration coefficient (C) with geological parameters (such as coal seam burial depth h), and the C value relies on experimental assumptions and is detached from actual engineering data. Fracture types are confused, and the quantitative relationship between propped fractures (L1), hydraulic fractures (L2), and monitoring fractures (L3) is not clearly distinguished, leading to blind fracturing design. Therefore, coalbed methane well fracturing requires accurate prediction of fracture size to optimize proppant dosage and fracturing fluid injection strategy, and reduce the cost of ineffective fracturing. In actual engineering, dynamic models based on geological parameters are urgently needed to improve prediction efficiency and reliability. Summary of the Invention

[0008] In order to solve the problem that it is difficult to accurately predict the size of cracks in coalbed methane well fracturing, the present invention provides a method for predicting the size of cracks in coalbed methane well fracturing, which mainly includes:

[0009] S1: Based on the PKN model, the relationship between the filtration coefficient and the burial depth is established to obtain the propped crack length;

[0010] S2: Based on the prop crack length, the relationship between the hydraulic crack length and the measured prop crack length is established;

[0011] S3: Based on the relationship between the hydraulic fracture length and the measured propped fracture length, the relationship between the microseismic monitoring fracture length and the measured propped fracture length is established. The scale of the CBM well hydraulic fracture can be obtained by the obtained propped fracture length, hydraulic fracture length and microseismic monitoring fracture length.

[0012] A computer device includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0013] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above method.

[0014] A computer program product includes a computer program or instructions, which implement the steps of the above method when the program or instructions are executed by a processor.

[0015] The technical solution provided by the present invention has the following beneficial effects: Based on the PKN model, the present invention establishes a relationship between the fluid loss coefficient and burial depth to obtain the propped fracture length; based on the propped fracture length, the present invention establishes a relationship between the hydraulic fracture length and the measured propped fracture length; based on the relationship between the hydraulic fracture length and the measured propped fracture length, the present invention establishes a relationship between the microseismic monitoring fracture length and the measured propped fracture length. The obtained propped fracture length, hydraulic fracture length, and microseismic monitoring fracture length can be used to accurately predict the scale of the hydraulic fracture in the coalbed methane well. By dynamically correcting the fluid loss coefficient and quantifying the proportional relationship between multiple fractures, the present invention significantly improves prediction accuracy and fracturing design efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0017] Figure 1 It is a schematic diagram of the range of three types of fractures formed by hydraulic fracturing in the background technology of the present invention;

[0018] Figure 2 Flowchart of a method for predicting the scale of fractures in a coalbed methane well hydraulic fracturing according to an embodiment of the present invention;

[0019] Figure 3 Schematic diagram of the relationship between the filtration coefficient and the burial depth in an embodiment of the present invention;

[0020] Figure 4 Schematic diagram of the relationship between the average length of a single wing of a microseismic monitoring crack and the burial depth in an embodiment of the present invention;

[0021] Figure 5 Schematic diagram of the relationship between the measured crack length and burial depth in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described in detail with reference to the accompanying drawings.

[0023] Example 1

[0024] The present invention selects the PKN model, which is more suitable for the situation that the hydraulic fracture in the coal seam is limited in height and width, extends far in the length direction, and has a large filtration loss.

[0025] In the PKN model, considering the filtration factor, the crack length (half-length) equation is:

[0026]

[0027] Quoting Nordgren, a mathematical model of fracture length and width that takes into account the effect of filtration:

[0028]

[0029] Get the equation

[0030]

[0031] Combining the initial conditions and boundary conditions, the support crack length can be obtained as:

[0032]

[0033] In the above formulas, C is the fracturing fluid loss coefficient, m / s 0.5 ; L is the length of the support crack, m; τ is the time when the liquid reaches x, s; t is the time, s; q is the flow rate at any point along the length of the crack, m 3 / s; Q is the construction displacement, m 3 / s; H is the crack height, m; w is the crack width at any point, m; A(t) is the crack area at time t, m 2 ;S p is the initial filtration loss of fracturing fluid, m 3 / m 2 ;q L is the fracturing fluid loss rate, m 2 / s; μ is the viscosity of Newtonian fluid, Pa·s; G is the shear elastic modulus of rock, Pa; v is the Poisson's ratio of rock; w(x, 0) is the maximum width of the crack at time t of the elliptical section at the crack mouth, m.

[0034] Please refer to Figure 2 , Figure 2 This is a flow chart of a method for predicting the scale of fractures in a coalbed methane well hydraulic fracturing according to an embodiment of the present invention, which specifically includes:

[0035] 1. Establish the relationship between filtration coefficient and burial depth

[0036] In formula (4), Q, t, and H are hydraulic fracturing construction parameters, which are obtained from the fracturing construction report and regional geological data in the study area. However, the filtration coefficient C is related to geological factors and cannot be directly obtained through data collection and underground observation. Through underground observation of coal mines of coalbed methane fracturing wells that have been exposed in the study area for many years, the spread range of fracturing sand is regarded as the length of the supporting crack. Substituting the supporting crack length and related construction parameters into formula (4), the filtration coefficient of the relevant coalbed methane well can be obtained. Through linear fitting, it is found that the filtration coefficient is related to the burial depth under the same geological conditions. The empirical formula for the relationship between the filtration coefficient and the burial depth is obtained as follows:

[0037] C=ah+b (5)

[0038] Substituting formula (5) into formula (4), the support crack length can be obtained as:

[0039]

[0040] Where h is the depth of coal seam, m; a and b are the coefficients of the linear equation respectively.

[0041] 2. Establish the relationship between hydraulic fracture length and measured support fracture length

[0042] After the surface CBM well is fracturing, as the coal mine face is excavated and advanced, coalbed water is collected at different locations and its water quality and ion concentration are measured to define the fracturing fluid range. At the same time, the length of the fracture propagation is observed. Based on statistical laws, the ratio of the hydraulic fracture length (L2) of the fracturing fluid propagation distance to the measured average length of the propagation fracture (L1) is determined as follows:

[0043]

[0044] Substituting the measured data, we can get:

[0045] L2=αL1 (8)

[0046] Where α represents the proportional coefficient between the hydraulic fracture length and the propped fracture length.

[0047] 3. Establish the relationship between microseismic monitoring crack length and measured support crack length

[0048] During surface coalbed methane well fracturing, microseismic crack length monitoring is performed. Because there is no significant correlation between the microseismic crack length and the measured crack length and coal seam depth (ground stress), this study uses statistical methods to represent the values of the two using average values. The average single-wing length of the cracks in the microseismic data, that is, the ratio of the microseismic crack length (L3) to the average length of all measured supporting cracks (L1), is:

[0049]

[0050] Substituting the measured data, we can get:

[0051] L3=βL1 (10)

[0052] At this point, based on the on-site fracturing construction parameters Q, t, and H, the propped fracture length (L1), hydraulic fracture length (L2), and microseismic monitoring fracture length (L3) can be obtained.

[0053] Where β represents the proportional coefficient between the length of the microseismic monitoring crack and the length of the supporting crack.

[0054] Case and verification

[0055] 1. Establish the relationship between filtration coefficient and burial depth

[0056] The method disclosed in the present invention is applicable to the 700m and shallow coal seams in the southern Qin area. Take the coal and coalbed methane co-mining area of the Qinshui Basin in Shanxi as an example. In formula (4), Q, t, and H are the construction parameters of the hydraulic fracturing project, which can be obtained by collecting data (Table 1). Substituting the support crack length and related construction parameters into formula (4), the filtration coefficient of the relevant coalbed methane well can be obtained. Through linear fitting, the empirical formula for the relationship between the filtration coefficient and the burial depth is obtained as follows: ( Figure 1 ):

[0057] C=-0.0001h+0.0764 (5)

[0058] Substituting formula (5) into formula (4), the support crack length can be obtained as:

[0059]

[0060] Where h is the depth of coal seam, m.

[0061] The relationship between the filtration coefficient C and the burial depth h is as follows: Figure 3 shown.

[0062] Table 1 Coalbed methane well parameters observed downhole

[0063]

[0064] 2. Relationship between hydraulic fracture length and support fracture length

[0065] After the fracturing is completed, as the working face is excavated and advanced, coal seam water is collected at different locations and the water quality and ion concentration are measured to define the range of the fracturing fluid. The propagation fracture length of the case well is 45m, and the fracturing fluid propagation distance or hydraulic fracture length is 144m, that is, the hydraulic fracture is 3.2 times the propagation fracture length. According to statistics from multiple wells, the propagation distance of the fracturing fluid is mostly about 3 times the proppant migration range. That is, the ratio of the hydraulic fracture length (L2) of the fracturing fluid propagation distance to the average length of the measured propagation fracture (L1) is:

[0066] α=3.00, then: L2=3.00L1

[0067] 3. Relationship between microseismic monitoring crack length and measured support crack length

[0068] According to the microseismic crack monitoring data obtained, see Table 2 for details:

[0069] Table 2 Statistics of crack lengths monitored by microseismic monitoring

[0070]

[0071] Table 2 shows that when the coal seam is 200-300 m deep, the average length of a single wing of the crack detected by microseismic monitoring is 78.87 m; when the coal seam is 300-400 m deep, the average length of a single wing of the crack detected by microseismic monitoring is 78.94 m; when the coal seam is 400-500 m deep, the average length of a single wing of the crack detected by microseismic monitoring is 80.15 m; when the coal seam is 500-600 m deep, the average length of a single wing of the crack detected by microseismic monitoring is 82.68 m; and when the coal seam is 500-600 m deep, the average length of a single wing of the crack detected by microseismic monitoring is 81.82 m. This shows that the average length of a single crack detected by microseismic monitoring varies little for every 100 m of depth, and the average length of a single wing of the crack detected in the statistical data is 79.78 m.

[0072] The coalbed methane well data collected based on downhole observations are detailed in Table 3:

[0073] Table 3 Statistics of measured support crack lengths in coalbed methane wells and coal mines

[0074]

[0075] Table 3 shows that when the coal seam is buried at a depth of 200-300m, the measured average fracture length is 27.5m; when it is buried at a depth of 300-400m, the measured average fracture length is 16.93m; when it is buried at a depth of 400-500m, the measured average half-fracture length is 21.26m; and when it is buried at a depth of 500-600m, the measured average half-fracture length is 19.8m. There is no significant correlation between the measured average half-fracture length and the depth; the average length of all measured fractures is 20.06m.

[0076] Since the microseismic monitoring crack length has no significant correlation with the measured crack length and coal seam burial depth (ground stress) ( Figure 4 , Figure 5 ), so this paper uses statistical methods to characterize the values of both using average values. The ratio of the average single-wing length of the cracks in the microseismic data, that is, the monitored crack length (L3) to the average length of all measured propped cracks (L1), is: β = 3.98, thus: L3 = 3.98L1.

[0077] 4. Crack length prediction model and its verification

[0078] In summary, the relationship between the measured propped crack length (L1), hydraulic crack length (L2), and microseismic monitoring crack length (L3) is:

[0079] L2=3.00L1,

[0080] L3=3.98L1,

[0081] And because the relationship between the support crack length is:

[0082]

[0083] Therefore, the empirical formula for the propagation distance of the fracturing fluid, that is, the length of the hydraulic fracture, is:

[0084]

[0085] The empirical formula for microseismic monitoring crack length is:

[0086]

[0087] This example was verified using three coalbed methane fracturing wells in the study area. The verification well parameters are shown in Table 4:

[0088] Table 4 Verification well parameters

[0089]

[0090] (1) Well No. 1: Microseismic data showed a fracture length of 75 m; a fracture profile was observed at a distance of 21.5 m from the wellbore.

[0091] (2) Well No. 2: Microseismic data showed that the fracture length was 83 m; fracture profiles were observed at 42 m and 47 m from the wellbore, and the proppant content in the fracture at 47 m was very low, so it can be assumed that the maximum proppant movement distance was 47 m.

[0092] (3) Well No. 3: Microseismic data showed that the fracture length was 88 m; downhole observations showed that the maximum proppant movement distance was 25 m.

[0093] The accuracy rate can clearly show the prediction accuracy of CBM well fracturing. The accuracy rate θ is expressed as the difference between 100% and the relative error, and the expression is:

[0094]

[0095] Where, is the monitoring value, and ω is the predicted value.

[0096] Example 2

[0097] A computer device includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0098] Example 3

[0099] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above method.

[0100] Example 4

[0101] A computer program product includes a computer program or instructions, which implement the steps of the above method when the program or instructions are executed by a processor.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for predicting the scale of fractures in a coalbed methane well, characterized in that: include: S1: Based on the PKN model, the relationship between the filtration coefficient and the burial depth is established to obtain the propped crack length; S2: Based on the prop crack length, the relationship between the hydraulic crack length and the measured prop crack length is established; S3: Based on the relationship between the hydraulic fracture length and the measured propped fracture length, the relationship between the microseismic monitoring fracture length and the measured propped fracture length is established. The scale of the CBM well hydraulic fracture can be obtained by the obtained propped fracture length, hydraulic fracture length and microseismic monitoring fracture length.

2. A method for predicting the scale of fractures in a coalbed methane well according to claim 1, characterized in that: In S1, the relationship between the filtration coefficient and the burial depth is: C=ah+b Among them, C is the fracturing fluid loss coefficient, h is the coal seam depth, and a and b are the coefficients of the linear equation.

3. A method for predicting the scale of fractures in a coalbed methane well according to claim 1, characterized in that: In S1, the calculation formula for the support crack length L is: Among them, Q is the construction displacement, H is the crack height, t is the time, h is the coal seam depth, and a and b are the coefficients of the linear equation.

4. A method for predicting the scale of fractures in a coalbed methane well according to claim 1, characterized in that: In S2, the relationship between the hydraulic fracture length and the measured propped fracture length is: L2=αL1 Where L2 represents the length of the hydraulic fracture, L1 represents the measured propped fracture length, and α represents the proportional coefficient between the hydraulic fracture length and the propped fracture length.

5. A method for predicting the scale of hydraulic fractures in a coalbed methane well according to claim 1, characterized in that: In S3, the relationship between the microseismic monitoring crack length and the measured support crack length is: L3=βL1 Where L3 represents the length of the microseismic monitoring crack, L1 represents the measured propping crack length, and β represents the proportional coefficient between the microseismic monitoring crack length and the propping crack length.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method for predicting the scale of fractures in a coalbed methane well hydraulic fracturing as described in any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that A computer program is stored, and when the program is executed by a processor, the steps of the method for predicting the scale of fractures in a coalbed methane well hydraulic fracturing are implemented as described in any one of claims 1 to 5.

8. A computer program product, characterized in that The method comprises a computer program or an instruction, which, when executed by a processor, implements the steps of the method for predicting the scale of fractures in a coalbed methane well hydraulic fracturing as described in any one of claims 1 to 5.

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